Crafting Smarter Interfaces with Anticipatory Design
Decision fatigue paralyzes users and leads to poor decision-making… here’s how you avoid it.
Giving users explicit choice is generally well-intentioned, but there’s an art to balancing autonomy and clarity. In attempting to represent the full range of options available, designers often think they’re being thoughtful and transparent, when in reality most users neither care for nor want the ‘additional fluff.’
Decision fatigue occurs when users are presented with too much information, or too many options, all at once. It is a real and pervasive consequence of poor UX, and negatively impacts the usability of any product/service/experience.
Unfortunately, products/services/experiences with an overbearing amount of options are all too prevalent. Perhaps because we’re used to interacting with many of them on a day to day basis, we overlook the fact that they could still be made simpler and more efficient.
As UX designer Miklos Philips writes on TopTal,
“Today, we’re still looking at two-dimensional screens and mostly use keyboards and mice for input; devices designed for interaction methods that were optimized for computers, not humans… It’s as if we’re using interaction models from the Flintstones’ era in a Jetsons’ world; they still rely on a lot of interaction from users (input) to move to the next step and display useful information (output).”
Consider the Adobe Suite for instance, which, according to the Reddit community consensus, performs surprisingly poorly in usability for a set of design tools.
What if instead Photoshop was able to suggest the right tool, at the right time, based on workflows, user preferences, context of the project, and so forth?
Designing anticipatory programs is the future of digital interfaces and product design. By pleasantly surprising users and eliminating unnecessary decision-making, anticipatory design can personalize experiences, increase retention, and win the hearts of your audience.
What ‘Anticipatory Design’ Is:
The term was first coined by HUGE CEO Aaron Shapiro in 2015 to describe a system designed to learn and adapt to user needs.
“Imagine a website, which knew you liked reading reviews by industry experts, automatically responding to your inclinations by linking to expert reviews. Meanwhile, someone else, who only cares about price, is shown price comparisons between the site and its competitors. In both cases, the (presumably positive) UX is the product of an anticipated and responsive design.”
-Mitchell Tweedie, Anticipatory Design: The Future of UX Design
This can manifest in many different ways, but the point is to streamline the process of performing certain functions while sparing users from functions they don’t care for. Here’s a great example using NYC’s MTA (subway) system:
Another example of anticipatory design is predictive text, which is an increasingly common feature among messaging and communications platforms. By relying on contextual clues and texting history, everyday systems like texting and emailing have evolved to streamline workflows and even present us with options we wouldn’t have come up with ourselves.
From the proliferation of automatic breaks in cars to intricately architected web experiences, we’re beginning to see the anticipatory design trend take off. As with any relatively new design trend, there’s still a few misconceptions to correct.
What Anticipatory Design Isn’t
In understanding what anticipatory design is, it also helps to understand what it isn’t.
“It can be argued that any form of user centered design is anticipatory design, because the designer creates something in anticipation of a user reaction. A flat steel plate on the door is put expecting users to understand that its a “push” door and not a “pull” door. A button on the digital interface is put there expecting users will understand and click it. A designer in each of these case anticipated needs, expectations and wishes of the users.
But, thats not true. Most of the systems and interfaces we design today are not truly anticipatory, we can call them “reactive”, they react to changes in the present. Whereas anticipatory interface’s present behaviour considers aspects of past, present and future.”
Anticipatory Interfaces — Deconstructing the principles by Sajid Saiyed
Conflating designs that guide users towards certain actions with ones that change predictively is a common misconception. Tutorials are a good example of misconstruing anticipatory design, as they serve to acquaint new users, but there’s nothing predictive about them otherwise.
Essentially, anticipatory design is fluid, and morphs predictively to shorten the amount of time and effort needed to accomplish a certain task.
Huge’s Aaron Shapiro defines anticipatory design as a method of simplifying processes by responding to needs one step ahead of the user’s decisions, i.e. responding to user needs they haven’t expressed yet.
How to Design Experiences that Anticipate Intent:
Conceptually speaking, anticipatory design originates from how the systems we as people employ when anticipating an event. Our responses to these events are triggered either in anticipation of an event (Pre-Event) or are evoked by an event (Post-Event). Right now, most designs exist as the latter response, relying on user to input to react accordingly.
Here’s a flow chart breaking down the various types of interface responses:
Within anticipatory systems, event related systems fall into two categories: expectatory and preparatory. By learning what to expect (expectatory) and triggering events to train users and in turn learn if they like it or not (preparatory), we can design fluid interfaces that evolves with and prepares for the user’s interaction.
Designing anticipatory interfaces can take many forms, from micro-interactions to suggestion algorithms to shuffling layouts. The key to prioritizing which area would benefit the most from adding a predictive layer is to figure out where users are having the most trouble or how you can streamline the time it takes to achieve a task.
You can achieve further clarity on which area to prioritize by considering the information below:
By considering intent, baseline, effect, and sustainment, designers can effectively design anticipatory scenarios that streamline tasks and help users achieve their goals.
Its important to state that as with any design concept, there’s a time and place for when to use it. There are certainly downsides to anticipatory design that should weigh in on the decision of when (or when not) to apply it.
The Downside of Anticipatory Design & How to Mitigate it:
The danger of being wrong is relative to the context in which anticipatory design is being applied. In certain industries, anticipatory design is a high-risk proposition: in the finance and health sectors for instance, the cost of being wrong is generally much higher than it is for the entertainment industry.
Understanding your users’ needs and expectations is key to determining what risks to take and how willing and/or able your users will be to forgive such errors. A bad Netflix autoplay is easy to overlook, whereas sensitive poor judgement in medical issues can lead to further complications.
Here is how you should go about your design work based on the probability of being right and the cost of being wrong:
Creepy Data Privacy Issues:
There’s something to be said for the invasiveness of a product or service that seems to know you a little too well.
Since anticipatory design requires context, and context requires data, designers need to consider the implications of
“There is a general mistrust of users considering the discretion behind their data-housing. There is much skepticism due to studies around illegal data-distribution that affects the trust and willingness of users. A worrying attitude because it may inhibit the development around predictive UX… Automation will ask much more transparency from its users to estimate needs correctly. The current privacy-ecosystem is not sufficient and scalable in that regard.”
How Anticipatory Design Will Challenge Our Relationship with Technology by Joël van Bodegraven,
Lack of Empathy and Context:
“Algorithms are not capable of understanding the context and drivers behind certain decisions. If I, for example buy a Ferrari cap, the algorithm will not understand that this product reminds me of my dad and that my purchase decision is based on nostalgic feelings.”
Anticipatory Design by Joël van Bodegraven
There are many variables at play when a decision is being made, lots of which will go unrecognized by an algorithm that focuses on only the ones a designer was able to identify. Therefore, its critical to understand your user by continuously doing the human labor involved in recognizing and updating the variables an algorithm considers.
“Stuck in a Bubble”:
Rolling with the previous example, surprise and discovery are a genuine part of human nature that can be easily stripped away from us when choice is removed. There will be times when an anticipatory interface will show you exactly what you need, but omit the things you didn’t know you needed or wanted to experience. As such, it is as important to respect the emotional response of your experience as it is the navigability and frictionless-ness of your design.
As the UX world grows increasingly aware of anticipatory practices, we should expect to see more businesses, products and services adopt the conceptual framework (assuming we take even notice).
Amazon obtained a patent for ‘Anticipatory Shipping’ a few years back, which will analyze purchase behaviors and search patterns to predict your next order. This will enable the company to prep boxes of those items for you at a warehouse nearest to your location, before you even place that order. Should this prove successful, the project will take predictive analytics to the next level.
Similarly, Google’s Nest thermostat learns your schedule, preferences, energy expenditure and when you’re home to adjust temperature settings accordingly without the user having to give it any thought.
Evidently, we’re moving towards a world with less choice by design. In such a future, designers will need to consider where and when to enable manual input versus when to let the system take over, all on the basis of ethics, human emotions and behavior, and value to the user. All things considered, this will be sure to spark a surge of ways brands and consumers will interact, and will reshape the way (wo)man and machine interact with the growing prevalence of AI and Big Data.